Surbhi Goel

Surbhi Goel

Postdoc Researcher

Microsoft Research, New York City

I am a postdoctoral researcher at Microsoft Research NYC in the Machine Learning group.

My research interests lie at the intersection of theory and machine learning. I am particularly excited about building theoretical foundations for modern machine learning methods. My work attempts to understand the limitations of existing algorithms and design new provably efficient algorithms for several machine learning problems.

Prior to joining MSR, I obtained my Ph.D. in the Computer Science department at the University of Texas at Austin advised by Adam Klivans. My dissertation was awarded UTCS’s Bert Kay Dissertation award. My research was generously supported by the JP Morgan AI Fellowship and several fellowships from UT Austin. During my PhD, I visited IAS for the Theoretical Machine learning program and the Simons Institute for the Theory of Computing at UC Berkeley for the Foundations of Deep Learning program (supported by the Simons-Berkeley Research Fellowship). Before that, I received my Bachelors degree from Indian Institute of Technology (IIT) Delhi majoring in Computer Science and Engineering.

I am on the job market for positions starting in Fall 2022.

Download my resumé.

Interests
  • Theory
  • Machine Learning
Education
  • PhD in Computer Science, 2020

    University of Texas at Austin

  • MS in Computer Science, 2019

    University of Texas at Austin

  • BTech in Computer Science and Engineering, 2015

    Indian Institute of Technology, Delhi

Recent Publications & Preprints

Investigating the Role of Negatives in Contrastive Representation Learning
Gone Fishing: Neural Active Learning with Fisher Embeddings
Acceleration via Fractal Learning Rate Schedules
Statistical Estimation from Dependent Data
Tight Hardness Results for Training Depth-2 ReLU Networks

Outreach

Co-organizer
Co-founded this mentorship initiative for the learning theory community. Co-organized mentorship workshops at ALT 2021 and COLT 2021.

Professional Services

Program Committee
Virtual Experience Chair
Program Committee
Program Committee